머신러닝 · GitHub

Manuscript of the book "Supervised Machine Learning for Text Analysis in R" by Emil Hvitfeldt and Julia Silge

Pytorch implementation of Neural Processes for functions and images :fireworks:

Six snippets of code that made deep learning what it is today.

Tensorflow implementation of the Vision Transformer (An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale)

Tensorflow 2.0 implementation of the paper: A Fully Convolutional Neural Network for Speech Enhancement

Code for Iterative Reasoning Paper (CVPR 2018)

Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks

⚠️ DEPRECATED. The work in this repository was merged into the main TPOT project as version 1.0. Please visit the active repository here: https://github.com/EpistasisLab/tpot/tree/main A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

Deep Learning Specialization by Andrew Ng on Coursera - My Completed Coursework Repo - All 5 Courses

Robust QR Detector based on YOLOv8

Official implementations for "Action2Motion: Conditioned Generation of 3D Human Motions (ACM MultiMedia 2020)"

TensorFlow tutorial on Generative Adversarial Models

Crash course to master gradient-based machine learning. Also secretly a JAX course in disguise!

Exploration of different solutions to action recognition in video, using neural networks implemented in PyTorch.

Codes for weekly challenges on Deep Learning by Siraj

My repo for training neural nets using pytorch-lightning and hydra

A numpy-only implementation of a Convolutional Neural Network, from the ground up.

A curated list of Earth Science's Artificial Intelligence (AI) tutorials, notebooks, software, datasets, courses, books, video lectures and papers. Contributions most welcome.

ArcGIS built-in python raster functions for deep learning to get you started fast.

Multi-language Analyze text in 26 Cantonal Swiss German, Italian, German, Chinese (simplified), French, Italian. pply natural language understanding (NLU) to their applications with features including sentiment analysis, entity analysis, entity sentiment analysis, content classification, and syntax analysis.

This is an LSTM stock prediction using Tensorflow with Keras on top.

A certifiable defense against adversarial examples by training neural networks to be provably robust

Discover, download, compile & launch different image processing & style transfer CoreML models on iOS.

📌 Papers, guides, and mentor interviews on applying machine learning for ApplyingML.com—the ghost knowledge of machine learning.